How to use this Blog?

This blog is to complement my lectures on medical statistics for both undergraduate (FF2613) and postgraduate (FK6163) in Faculty of Medicine, Universiti Kebangsaan Malaysia.

So if you are a medical undergraduate, looking for notes and practicals on medical statistics, to start, please click on the FF2613 button as illustrated below.

clickff2613

So if you are a medical postgraduate, looking for notes and practicals on medical statistics, to start, please click on the FK6163 button as illustrated below.

clickfk6163

So if you are a medical researcher, looking for notes and tools for sample size calculation, to start, please click on the “Sample Size” button as illustrated below.

clicksamplesize

Some of the “Download” medical statistics notes pages are protected by password. The passwords are available from your respective Facebook group page. For FF2613, the passwords are shared HERE. For FK6163, the passwords are shared HERE.

If you want to be able to read the notes only, they are also available from SlideShare.

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Protected: FFFK6163 – Computer Based Examination on Analysis Using SPSS

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Protected: FFFK6193 – Computer Based Examination on Analysis Using R Studio

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FFFK6193 – Computer Based Analysis Using R Studio

Use the notes from here – https://www.slideshare.net/mobile/drtamil/introduction-to-data-analysis-with-r-and-r-studio

Use your browser to download your Excel data from the following link;

Click HERE

Do the following analysis on the data using R Studio then submit your answers via this LINK.

A study to identify factors that can cause small for gestational age (SGA) was conducted. Among the factors studied were the mothers’ body mass index (BMI). It is believed that mothers with lower BMI were of higher risk to get SGA babies.

1. Create a new variable mBMI (Mothers’ Body Mass Index) from the mothers’ HEIGHT (in metre) & WEIGHT (first trimester weight in kg). mBMI = weight in kg/(height in metre)2. Calculate the following for mBMI;

  • Mean
  • Standard deviation

Copy and paste your answers into your Word file.

2. Create a new variable OBESCLAS (Classification of Obesity) from mBMI. Use the following cutoff point;

  • <20 = Underweight
  • 20 – 24.99 = Normal
  • 25 or larger = Overweight

Create a frequency table for OBESCLAS. Copy and paste the table into your Word file.

3. Conduct the appropriate statistical test to test whether there is any association between OBESCLAS (Underweight/Normal/Overweight) and OUTCOME.

Copy and paste the appropriate tables along with the interpretation into your Word file.

4. Conduct the appropriate statistical test to test whether there is any association between BMI and OUTCOME.

Copy and paste the appropriate tables along with the interpretation into your Word file.

5. Conduct the appropriate statistical test to find any association between OBESCLAS (Underweight/Normal/Overweight) and BIRTHWGT.

Copy and paste the appropriate tables along with the interpretation into your Word file.

6. Assuming that both variables mBMI & BIRTHWGT are normally distributed,

  • conduct an appropriate statistical test to prove the association between the two variables.
  • Demonstrate the association using the appropriate chart. Determine the coefficient of determination.

Copy and paste the above charts and your answers into your Word file.

7. Conduct Simple Linear Regression using BIRTHWGT as the dependent variable. Try to come out with a formula that will predict the baby’s birth weight based on the mother’s BMI.

y = a + bx

Copy and paste the appropriate tables and supporting chart along with the interpretation into your Word file.

Copy all the text (Ctrl-A, Ctrl-C) in the Command window and paste (Ctrl-V) into your Word file.

Save your Word file using your matric number as its filename i.e. P163341.doc. Now transfer your answers from the Word file onto this online form at LINK. Upon finishing, please click the SUBMIT button to submit your answers.

Just in case your answers go missing in the ether of cyberspace, please upload that file here in the Google Form.

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Protected: FK6193 – 3rd Assignment

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Protected: FFFK6193 – Assignment 2 – GLM

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Protected: FK6193 – Assignment 1 – Rasch Dichotomous

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Protected: FFFF3618 – Computer Based Examination

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Protected: UM Oncology Stats Short Course 09/02/2020

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Protected: FK6342 – Policies & Standards of HIS

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FF2613 – Project Presentation 2019

Lab 1

Lab2

Lab 3

Lab 4

Lab 5

Lab 6

Lab 7

Lab 8

Lab 9

Lab 10

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